trpValueFunction: Transform a decision Matrix into a trp value matrix

In avilesd/productConfig: Tools to analyze behavioral patterns from Product Configurators

Description

This function is based on the value function of the tri-reference point (trp) theory. It is an auxiliary function, which intends to facilitate the work and readability of trpValueMatrix.oneAttr, trpValueMatrix. It takes a matrix and the three given reference points (MR, SQ, G) as a vector tri.refps and applys the trp value function trpValueFunction to each element of the matrix. Also takes into account the for free beta parameters of the function.

Usage

trpValueFunction(aMatrix, triRefps, beta_f = 5, beta_l = 1.5, beta_g = 1,
  beta_s = 3)

Arguments

aMatrix	a non-empty matrix, tipically with one column since this function is called one attribute at a time by trpValueMatrix.oneAttr.
mr	numeric - Minimum Requirements is the lowest reference point
sq	numeric - Status Quo reference point
g	numeric - Goal reference point
beta(s)	numeric arguments representing the psychological impact of an outcome equaling failer (_f), loss (_l), gain (_g) or success (_s). Default values are taken from our reference paper (5,1,1,3). See details.

Details

The functions test for MR < SQ < G

The beta arguments are important arguments that give form to the value function proposed in [1]. A higher number represents a higher relative psychological impact to the decision maker. Since in [1] it is assumed that the reference point 'Minimum Requierment' has a greater impact when is not reached (failure aversion), it should have a higher beta, so in general beta_f > beta_l > beta_g > beta_s. See our reference paper for a detailed theoretical background.

Value

returns a matrix with the outputs of the trp value function for each of its elements

References

[1] Wang, X. T.; Johnson, Joseph G. (2012) A tri-reference point theory of decision making under risk. Journal of Experimental Psychology

[2]Wang, X. T.; Johnson, Joseph G. (2012) Supplemental Material for: A tri-reference point theory of decision making under risk. Journal of Experimental Psychology

Examples

# Runnable
trpValueFunction(aMatrix = matrix(1:6, 2, 3), triRefps = c(2,3,4.5))
trpValueFunction(matrix(1:16, 16, 1), triRefps = c(4, 8.9, 12.5), beta_f = 7)

avilesd/productConfig documentation built on May 11, 2019, 4:08 p.m.